Aspects of the disclosure are related to computing hardware and software technology, and in particular to industrial automation applications.
Industrial controllers and their associated I/O devices are central to the operation of modem automation systems. These controllers interact with field devices on the plant floor to control automated processes relating to such objectives as product manufacture, material handling, batch processing, supervisory control, and other such applications. Industrial controllers store and execute user-defined control programs to effect decision-making in connection with the controlled process. Such programs can include, but are not limited to, ladder logic, sequential function charts, function block diagrams, structured text, or other such programming structures.
Because of the large number of system variables that must be monitored and controlled in near real-time, industrial automation systems often generate vast amounts of near real-time data. In addition to production statistics, data relating to machine health, alarm statuses, operator feedback (e.g., manually entered reason codes associated with a downtime condition), electrical or mechanical load over time, and the like are often monitored, and in some cases recorded, on a continuous basis. This data is generated by the many industrial devices that can make up a given automation system, including the industrial controller and its associated I/O, telemetry devices for near real-time metering, motion control devices (e.g., drives for controlling the motors that make up a motion system), visualization applications, lot traceability systems (e.g., barcode tracking), etc. Moreover, since many industrial facilities operate on a 24-hour basis, their associated automation systems can generate a vast amount of potentially useful data at high rates. For an enterprise with multiple plant facilities, the amount of generated automation data further increases
The large quantity of data generated by modern automation systems makes it possible to apply a broad range of plant analytics to the automation systems and processes that make up an industrial enterprise or business. Reports, charts, and other human-readable formats are often available or may be created for plant personnel and others wishing to monitor and review the generated data in either a real-time mode or at a later time after the data has been stored.
In one scenario, applications and other software implemented to acquire the industrial automation data for purposes of such as those described above must be able to discover where the data stores are located in the system, be able to interact via the protocol of each data store, and appropriately translate/interpret the data from each data store in order to acquire the data stored therein. Referring to FIG. 1, a prior art data acquisition environment 2 includes a computing device 4 accesses or executes an application 6 configured to acquire data for reporting purposes, for example. The data to be reported may be stored, in this example, in any one or all of a plurality of data storages such as a historian database 8, a file system on a hard drive 10, and a relational database 12 such as a Structured Query Language (SQL) database. To acquire or obtain the relevant stored data, application 6 must know not only how to find each of the data storages 8-12, but it must also be able to communicate with each of the data storages 8-12 in their respective protocols. This requires the application 6 to know the protocols of every data storage location from which the data is to be obtained. If data to be acquired by the application 6 is changed to a different protocol, whether known or unknown to the application 6, or is changed to a different location, the application 6 must be modified in order to track the change. Accordingly, any protocol or location change to any of the data storages 8-12 requires the application to be changed and updated as well.
The above-described deficiencies are merely intended to provide an overview of some of the problems of conventional systems, and are not intended to be exhaustive. Other problems with conventional systems and corresponding benefits of the various non-limiting embodiments described herein may become further apparent upon review of the following description.